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matlab function 'trapz  (MathWorks Inc)


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    MathWorks Inc matlab function 'trapz
    Matlab Function 'Trapz, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+trapz/pm40338284-119-23-21
    Average 90 stars, based on 1 article reviews
    matlab function 'trapz - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    Inhibition:

    Article Title: Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins
    Article Snippet: The area under the curve was calculated using the “trapz” function in MATLAB and the maximum peak or minima by detecting the largest positive or negative value and calculating the average for the 0.25 s on either side of this value (to reduce the impact of “noise spikes”).

    Article Title: Pre-sleep alpha brain entrainment by audio or visual stimulation for chronic widespread pain and sleep disturbance: A randomised crossover feasibility trial.
    Article Snippet: The resultant oscillatory component of the signal was subsequently J ur na l P re -p ro of integrated across the alpha band range (8–13 Hz) with the MATLAB 'trapz' function, log transformed and multiplied by 20 to give a value in decibels (dB).

    Article Title: Visualizing pulp fibers using X-ray tomography: Enhancing the contrast by labeling with iron oxide nanoparticles and the use of immersion oil
    Article Snippet: Even with some overlapping (estimated to be 3.0 % of the total area, using the function “trapz” on Matlab), segmentation using a thresholding value (vertical dotted line) is possible due to the “valley” in the PDF of the entire sample, making the combination of labeled fibers and oil immersion suitable for fiber segmentation [29,45,46].

    Article Title: Electrical stimulation of neuroretinas with 3D pyrolytic carbon electrodes.
    Article Snippet: For the estimation of the number of contributing neurons to the compound, the area under spikes was calculated using trapezoidal numerical integration with the ‘trapz’ function in Matlab.

    Article Title: Synaptic plasticity rules driving representational shifting in the hippocampus.
    Article Snippet: Synaptic plasticity is widely thought to support memory storage in the brain, but the rules determining impactful synaptic changes in vivo are not known.. We considered the trial-by-trial shifting dynamics of hippocampal place fields (PF) as an indicator of ongoing plasticity during memory formation and familiarization.. By implementing different plasticity rules in computational models of spiking place cells and comparing them to experimentally measured PFs from mice navigating familiar and new environments, we found that behavioral timescale synaptic plasticity (BTSP), rather than Hebbian spike-timing-dependent plasticity (STDP), best explains PF shifting dynamics.

    Article Title: Characterizing vascular function in mouse models of Alzheimer’s disease, atherosclerosis, and mixed Alzheimer’s and atherosclerosis
    Article Snippet: For each individual trial, the area under the curve (AUC) of the hemodynamic and locomotion responses was assessed during and just beyond the stimulation period (5 to 10 s for 2s stimulation or 10 to 30 s for 16 s stimulation) using the “trapz” function in MATLAB, and the maximum peak by finding the largest value reached during this period.

    Control:

    Article Title: Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins
    Article Snippet: The area under the curve was calculated using the “trapz” function in MATLAB and the maximum peak or minima by detecting the largest positive or negative value and calculating the average for the 0.25 s on either side of this value (to reduce the impact of “noise spikes”).

    Article Title: Pre-sleep alpha brain entrainment by audio or visual stimulation for chronic widespread pain and sleep disturbance: A randomised crossover feasibility trial.
    Article Snippet: The resultant oscillatory component of the signal was subsequently J ur na l P re -p ro of integrated across the alpha band range (8–13 Hz) with the MATLAB 'trapz' function, log transformed and multiplied by 20 to give a value in decibels (dB).

    Article Title: Visualizing pulp fibers using X-ray tomography: Enhancing the contrast by labeling with iron oxide nanoparticles and the use of immersion oil
    Article Snippet: Even with some overlapping (estimated to be 3.0 % of the total area, using the function “trapz” on Matlab), segmentation using a thresholding value (vertical dotted line) is possible due to the “valley” in the PDF of the entire sample, making the combination of labeled fibers and oil immersion suitable for fiber segmentation [29,45,46].

    Article Title: Electrical stimulation of neuroretinas with 3D pyrolytic carbon electrodes.
    Article Snippet: For the estimation of the number of contributing neurons to the compound, the area under spikes was calculated using trapezoidal numerical integration with the ‘trapz’ function in Matlab.

    Article Title: Synaptic plasticity rules driving representational shifting in the hippocampus.
    Article Snippet: Synaptic plasticity is widely thought to support memory storage in the brain, but the rules determining impactful synaptic changes in vivo are not known.. We considered the trial-by-trial shifting dynamics of hippocampal place fields (PF) as an indicator of ongoing plasticity during memory formation and familiarization.. By implementing different plasticity rules in computational models of spiking place cells and comparing them to experimentally measured PFs from mice navigating familiar and new environments, we found that behavioral timescale synaptic plasticity (BTSP), rather than Hebbian spike-timing-dependent plasticity (STDP), best explains PF shifting dynamics.

    Article Title: Characterizing vascular function in mouse models of Alzheimer’s disease, atherosclerosis, and mixed Alzheimer’s and atherosclerosis
    Article Snippet: For each individual trial, the area under the curve (AUC) of the hemodynamic and locomotion responses was assessed during and just beyond the stimulation period (5 to 10 s for 2s stimulation or 10 to 30 s for 16 s stimulation) using the “trapz” function in MATLAB, and the maximum peak by finding the largest value reached during this period.

    Standard Deviation:

    Article Title: Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins
    Article Snippet: The area under the curve was calculated using the “trapz” function in MATLAB and the maximum peak or minima by detecting the largest positive or negative value and calculating the average for the 0.25 s on either side of this value (to reduce the impact of “noise spikes”).

    Article Title: Pre-sleep alpha brain entrainment by audio or visual stimulation for chronic widespread pain and sleep disturbance: A randomised crossover feasibility trial.
    Article Snippet: The resultant oscillatory component of the signal was subsequently J ur na l P re -p ro of integrated across the alpha band range (8–13 Hz) with the MATLAB 'trapz' function, log transformed and multiplied by 20 to give a value in decibels (dB).

    Article Title: Visualizing pulp fibers using X-ray tomography: Enhancing the contrast by labeling with iron oxide nanoparticles and the use of immersion oil
    Article Snippet: Even with some overlapping (estimated to be 3.0 % of the total area, using the function “trapz” on Matlab), segmentation using a thresholding value (vertical dotted line) is possible due to the “valley” in the PDF of the entire sample, making the combination of labeled fibers and oil immersion suitable for fiber segmentation [29,45,46].

    Article Title: Electrical stimulation of neuroretinas with 3D pyrolytic carbon electrodes.
    Article Snippet: For the estimation of the number of contributing neurons to the compound, the area under spikes was calculated using trapezoidal numerical integration with the ‘trapz’ function in Matlab.

    Article Title: Synaptic plasticity rules driving representational shifting in the hippocampus.
    Article Snippet: Synaptic plasticity is widely thought to support memory storage in the brain, but the rules determining impactful synaptic changes in vivo are not known.. We considered the trial-by-trial shifting dynamics of hippocampal place fields (PF) as an indicator of ongoing plasticity during memory formation and familiarization.. By implementing different plasticity rules in computational models of spiking place cells and comparing them to experimentally measured PFs from mice navigating familiar and new environments, we found that behavioral timescale synaptic plasticity (BTSP), rather than Hebbian spike-timing-dependent plasticity (STDP), best explains PF shifting dynamics.

    Article Title: Characterizing vascular function in mouse models of Alzheimer’s disease, atherosclerosis, and mixed Alzheimer’s and atherosclerosis
    Article Snippet: For each individual trial, the area under the curve (AUC) of the hemodynamic and locomotion responses was assessed during and just beyond the stimulation period (5 to 10 s for 2s stimulation or 10 to 30 s for 16 s stimulation) using the “trapz” function in MATLAB, and the maximum peak by finding the largest value reached during this period.



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    MathWorks Inc matlab's 'trapz' function
    Rectified soleus electromyography (EMG) traces (mean of 30 repetitions) from a control participant illustrating the heteronymous excitation (blue area) and inhibition (red area) from femoral nerve (FN) stimulation (2 × motor threshold, MT) onto ongoing soleus (SOL) EMG. Onset and offset latencies for excitation and inhibition are marked with blue and red circles, respectively. The solid horizontal black line represents the mean SOL background EMG, while the dashed horizontal line indicates one standard deviation below the mean. FN stimulation involved a single square pulse of 1 ms duration, resulting in a stimulation artifact (dashed vertical line). Excitation and inhibition areas (depicted as shaded blue and red regions, respectively) were quantified <t>using</t> <t>MATLAB’s</t> <t>‘trapz’</t> function, referenced to the mean background EMG. The duration was determined from the onset and offset timepoints
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    Image Search Results


    Rectified soleus electromyography (EMG) traces (mean of 30 repetitions) from a control participant illustrating the heteronymous excitation (blue area) and inhibition (red area) from femoral nerve (FN) stimulation (2 × motor threshold, MT) onto ongoing soleus (SOL) EMG. Onset and offset latencies for excitation and inhibition are marked with blue and red circles, respectively. The solid horizontal black line represents the mean SOL background EMG, while the dashed horizontal line indicates one standard deviation below the mean. FN stimulation involved a single square pulse of 1 ms duration, resulting in a stimulation artifact (dashed vertical line). Excitation and inhibition areas (depicted as shaded blue and red regions, respectively) were quantified using MATLAB’s ‘trapz’ function, referenced to the mean background EMG. The duration was determined from the onset and offset timepoints

    Journal: Journal of NeuroEngineering and Rehabilitation

    Article Title: Heteronymous feedback from quadriceps onto soleus in stroke survivors

    doi: 10.1186/s12984-025-01572-5

    Figure Lengend Snippet: Rectified soleus electromyography (EMG) traces (mean of 30 repetitions) from a control participant illustrating the heteronymous excitation (blue area) and inhibition (red area) from femoral nerve (FN) stimulation (2 × motor threshold, MT) onto ongoing soleus (SOL) EMG. Onset and offset latencies for excitation and inhibition are marked with blue and red circles, respectively. The solid horizontal black line represents the mean SOL background EMG, while the dashed horizontal line indicates one standard deviation below the mean. FN stimulation involved a single square pulse of 1 ms duration, resulting in a stimulation artifact (dashed vertical line). Excitation and inhibition areas (depicted as shaded blue and red regions, respectively) were quantified using MATLAB’s ‘trapz’ function, referenced to the mean background EMG. The duration was determined from the onset and offset timepoints

    Article Snippet: Excitation and inhibition areas (depicted as shaded blue and red regions, respectively) were quantified using MATLAB’s ‘trapz’ function, referenced to the mean background EMG.

    Techniques: Control, Inhibition, Standard Deviation